Chapter 4 LAGOS Spatial Analysis
4.1 Loading in data
4.1.1 First download and then specifically grab the locus (or site lat longs)
# #Lagos download script
# LAGOSNE::lagosne_get(dest_folder = LAGOSNE:::lagos_path())
#Load in lagos
lagos <- lagosne_load()
#Grab the lake centroid info
lake_centers <- lagos$locus
# load('lake_centers.Rdata')4.1.2 Convert to spatial data
#Look at the column names
#names(lake_centers)
#Look at the structure
#str(lake_centers)
#View the full dataset
#View(lake_centers %>% slice(1:100))
spatial_lakes <- st_as_sf(lake_centers,coords=c('nhd_long','nhd_lat'),
crs=4326) %>%
st_transform(2163)
#Subset for plotting
subset_spatial <- spatial_lakes %>%
slice(1:100)
subset_baser <- spatial_lakes[1:100,]
#Dynamic mapviewer
mapview(subset_spatial)4.1.3 Subset to only Minnesota
states <- us_states()
#Plot all the states to check if they loaded
#mapview(states)
minnesota <- states %>%
filter(name == 'Minnesota') %>%
st_transform(2163)
#Subset lakes based on spatial position, mutate state name
minnesota_lakes <- spatial_lakes[minnesota,] %>%
mutate(name = "Minnesota")
#Plotting the first 1000 lakes
minnesota_lakes %>%
arrange(-lake_area_ha) %>%
slice(1:1000) %>%
mapview(.,zcol = 'lake_area_ha')4.3 1) Show a map outline of Iowa and Illinois (similar to Minnesota map upstream)
# Grab both Iowa and Illinois state codes
iowa_illinois <- states %>%
filter(name %in% c("Iowa","Illinois")) %>%
st_transform(2163)
# Isolate lakes from Iowa and Illinois
iowa_illinois_lakes <- spatial_lakes[iowa_illinois,]
# Display the Outline
mapview(iowa_illinois, col.regions = "chartreuse4")4.4 2) Subset LAGOS data to these sites, how many sites are in Illinois and Iowa combined? How does this compare to Minnesota?
# Give an output statement on the sites in Iowa + Illinois vs. Minnesota
print(paste("There are", nrow(iowa_illinois_lakes), "lakes in Iowa and Illinois, and", nrow(minnesota_lakes), "lakes in Minnesota."))## [1] "There are 16466 lakes in Iowa and Illinois, and 29038 lakes in Minnesota."4.5 3) What is the distribution of lake size in Iowa vs. Minnesota?
- Here I want to see a histogram plot with lake size on x-axis and frequency on y axis (check out geom_histogram)
# Isolate Iowa lakes and mutate state name
iowa <- iowa_illinois %>% filter(name == "Iowa")
iowa_lakes <- spatial_lakes[iowa,] %>%
mutate(name = "Iowa")
iowa_minnesota_lakes <- rbind(iowa_lakes, minnesota_lakes)
p1 <- ggplot(iowa_lakes, aes(lake_area_ha)) +
geom_histogram(position = "dodge", color = "darkblue", fill = "dodgerblue4", binwidth = 0.04) +
theme(axis.title.x = element_blank()) + scale_x_log10() +
labs(title = "Distibution of Iowa lakes", y = "Count")
p2 <- ggplot(minnesota_lakes, aes(lake_area_ha), ) +
geom_histogram(position = "dodge", color = "darkblue", fill = "dodgerblue4", binwidth = 0.06) +
theme() + scale_x_log10() +
labs(title = "Distibution of Minnesota lakes", y = "Count", x = "Lake Area (Hectares)")
grid::grid.draw(rbind(ggplotGrob(p1), ggplotGrob(p2)))
## ^First solution before Matt told me to facet wrap.
# Facet wrap graph by state name.
p3 <- ggplot(iowa_minnesota_lakes, aes(x = lake_area_ha)) +
geom_histogram(position = "dodge", color = "darkblue", fill = "dodgerblue4", binwidth = 0.04) +
scale_x_log10() +
labs(title = "Distibution of Minnesota and Iowa lakes", y = "Count", x = "Lake Area (Hectares)") +
facet_wrap(~name, ncol = 1)
p3